Chinese Prompt Collection for AI Coding Tools: An Essential Reference for Developers
An open-source project collecting and translating system prompts from major AI coding tools into Chinese.
A GitHub project called "system-prompts-and-models-of-ai-tools-chinese" systematically collects system prompts from AI coding tools like Cursor, Devin, and VSCode Agent, providing Chinese translations and interpretations. With 1,120+ Stars, it helps Chinese-speaking developers understand AI tool internals, write better custom Rules, and stay updated on prompt changes across tools.
Project Overview
As AI-assisted programming becomes increasingly mainstream, a GitHub open-source project called "system-prompts-and-models-of-ai-tools-chinese" is rapidly gaining popularity in the Chinese developer community. The project systematically collects and organizes system prompts from major AI coding tools such as Cursor, Devin, and VSCode Agent, providing Chinese translations and interpretations. It serves as a valuable reference for Chinese-speaking developers to deeply understand and efficiently use these tools.
As of now, the project has earned 1,120 Stars and 210 Forks, reflecting the strong interest within the Chinese developer community in understanding the underlying mechanisms of AI coding tools.
Why Are System Prompts So Important?
Understanding the "Operating System" of AI Coding Tools
System prompts are the core soul of AI coding tools. They determine how an AI assistant understands your code, generates suggestions, and interacts with the development environment. Understanding these prompts is like getting the "user manual" for AI coding tools — you can make more precise requests to the AI and better understand its output logic.
From "Black Box Usage" to "Transparent Understanding"
Most developers passively accept AI suggestions when using Cursor or GitHub Copilot. But once you understand the design logic behind system prompts, you can:
- Write more targeted custom Rules to improve AI output quality
- Understand why AI excels in certain scenarios but falls short in others
- Draw inspiration from these prompt designs to optimize AI integration in your own projects
Major Tools Covered by the Project
Cursor
As the hottest AI code editor on the market, Cursor's system prompts reveal the underlying logic of how it handles code completion, multi-file editing, and user conversations. The Cursor prompts included in the project help developers write more effective .cursorrules files.
Devin
Often called an "AI software engineer," Devin's system prompts demonstrate how an autonomous coding Agent is designed — including instruction design for task decomposition, code execution, error handling, and complete workflows.
VSCode Agent
Microsoft's AI Agent integration in VS Code showcases a design philosophy for coordinating AI capabilities with developer workflows within a traditional IDE environment.
Practical Value for Chinese-Speaking Developers
Lowering the Language Barrier
Original system prompts are typically written in English and contain extensive technical terminology and specific formatting requirements. The project's Chinese translations and annotations allow developers who are less comfortable with English technical documentation to get started quickly.
Reference Templates for Custom Rules
The project's continuously updated Chinese coding Rules provide ready-to-use templates. Whether you're working on frontend development, backend services, or data analysis, you can find Rules configuration references suited to your tech stack.
Keeping Up with AI Coding Tool Updates
The project commits to continuous updates, meaning that when tools like Cursor or Copilot release new versions and adjust their system prompts, Chinese-speaking developers can access the latest information immediately.
How to Use This Project to Boost Your Coding Efficiency
- Learn prompt design patterns: Study these carefully crafted system prompts to learn how to give AI clear and effective instructions
- Customize personal Rules: Based on the templates provided, create personalized AI coding rules that match your programming habits and project requirements
- Compare design philosophies across tools: By horizontally comparing prompt differences between Cursor, Devin, and other tools, understand the strengths and weaknesses of different AI coding paradigms
- Contribute to the community: If you discover new AI tool prompts or have better Chinese translations, participate in the project through PRs
Conclusion
In 2025, as competition among AI coding tools reaches fever pitch, understanding the underlying prompt design of these tools has shifted from a "nice-to-have" to an "essential skill." This open-source project provides Chinese-speaking developers with a systematic learning path, helping them evolve from ordinary users of AI coding tools into power users. Whether you're a beginner just getting started with AI-assisted programming or a senior engineer looking to deeply customize your development experience, this project is worth bookmarking and following.
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